most citedData Generating Process to Evaluate Causal Discovery Techniques for Time Series Data

8 citations · 8 across the 1 of their papers we have counts for

collaborators

2 papers

stat.ML2021★ 8 cited

Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data

Andrew R. Lawrence, Marcus Kaiser, Rui Sampaio +1

Going beyond correlations, the understanding and identification of causal relationships in observational time series, an important subfield of Causal Discovery, poses a major chall…

stat.ML2018

DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures

Andrew R. Lawrence, Carl Henrik Ek, Neill D. F. Campbell

We present a non-parametric Bayesian latent variable model capable of learning dependency structures across dimensions in a multivariate setting. Our approach is based on flexible…